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510(k) Data Aggregation
(88 days)
The intra-aortic balloon is placed in the descending aorta just below the subclavian artery and is intended to improve cardiovascular functioning during the following situations:
Refractory ventricular failure
Cardiogenic shock
Unstable refractory angina
Impending infarction
Mechanical complications due to acute myocardial infarction
Ischemic related intractable ventricular arrhythmias
Cardiac support for high risk surgical patients and coronary angiography or angioplasty patients
Septic shock
Weaning from cardiopulmonary bypass
Interoperative pulsatile flow generation
Support for failed angioplasty and valvuloplasty
The intra-aortic balloon is placed in the descending aorta just below the subclavian artery and is intended to improve cardiovascular functioning during the following situations: Refractory ventricular failure Cardiogenic shock Unstable refractory angina Impending infarction Mechanical complications due to acute myocardial infarction Ischemic related intractable ventricular arrhythmias Cardiac support for high risk surgical patients and coronary angiography or angioplasty patients Septic shock Weaning from cardiopulmonary bypass Interoperative pulsatile flow generation Support for failed angioplasty and valvuloplasty
The provided text describes a 510(k) premarket notification for a medical device, the Datascope 8Fr. Co-Lumen (CL) Intra-Aortic Balloon (IAB) & Accessories. This submission focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than a clinical study with specific acceptance criteria and detailed performance metrics as one might find for a novel device or AI/software.
Therefore, the information typically expected for "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of an AI/software device is not applicable or available in this document. This submission is for a physical medical device (Intra-Aortic Balloon) seeking clearance based on its similarity to existing cleared devices, not on a performance study against predefined numerical acceptance criteria.
However, I can extract the relevant information from the document that addresses the spirit of your questions as much as possible within the context of a 510(k) for a physical medical device.
1. A table of acceptance criteria and the reported device performance
For a 510(k) submission, "acceptance criteria" are generally that the new device must be "substantially equivalent" to a predicate device in terms of intended use, technological characteristics, and safety and effectiveness. The "reported device performance" is a demonstration that this equivalence holds.
Acceptance Criteria (Implicit for 510(k)) | Reported Device Performance (Summary from Submission) |
---|---|
Intended Use: Device intended for same indications as predicate devices. | The device's indications for use are substantially equivalent to predicate devices (listed on page 7). |
Technological Characteristics: Differences in material composition and dimensional specifications do not affect safety or efficacy. | Differences in material composition and dimensional specifications have been demonstrated not to affect safety or efficacy of the device. (Page 4) |
Performance/Functionality: Functionality and performance comparable to currently marketed devices. | Results of in-vitro tests conducted demonstrate that the functionality and performance characteristics of the device are comparable to the currently marketed devices. (Page 4) |
Safety: Device is as safe as legally marketed predicate devices. | Implicitly demonstrated through substantial equivalence claim and in-vitro testing. (Page 4) |
Effectiveness: Device is as effective as legally marketed predicate devices. | Implicitly demonstrated through substantial equivalence claim and in-vitro testing. (Page 4) |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the document. The submission references "in-vitro tests" but does not detail the sample size or provenance of data for these tests. For a physical device 510(k), these tests are typically benchtop or mechanical tests, not clinical performance studies with patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This information is not applicable/provided. The concept of "ground truth" established by experts for a test set is typically relevant for diagnostic or AI/software devices where expert interpretation is part of the validation. For this physical IAB, the "ground truth" would be established by engineering specifications and in-vitro test results comparing against predicate device performance.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable/provided. Adjudication methods are typically used in clinical studies involving interpretation, which is not the primary mode of evaluation for this physical device in a 510(k) context.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
This information is not applicable. An MRMC study is designed for evaluating diagnostic devices, especially those with AI components, and the impact of AI on human reader performance. This submission is for a physical Intra-Aortic Balloon and does not involve AI or human readers for diagnostic tasks.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This information is not applicable. This question pertains to AI/software performance. The device is a physical intra-aortic balloon.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The document mentions "in-vitro tests" (Page 4). The "ground truth" for demonstrating substantial equivalence for a physical device like an IAB would primarily be based on engineering specifications, material science standards, and established performance characteristics of the predicate devices as measured through these in-vitro tests. There is no mention of expert consensus, pathology, or outcomes data being used as "ground truth" for the 510(k) submission itself, though clinical outcomes from general use of IABs would underpin the predicate devices' prior clearances.
8. The sample size for the training set
This information is not applicable. The device is a physical medical device, not an AI/machine learning algorithm that requires a "training set."
9. How the ground truth for the training set was established
This information is not applicable. As it's not an AI/ML device, there is no training set or ground truth in that context.
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